A logical approach to the management of object identifiers in non-conventional database management systems

Non-conventional database management systems are used to achieve a better performance when dealing with complex data. One fundamental concept of these systems is object identity (OID), because each object in the database has a unique identifier that is used to access and reference it in relationships to other objects. Two approaches can be used for the implementation of OIDs: physical or logical OIDs. In order to manage complex data, was proposed the Multimedia Data Manager Kernel (NuGeM) that uses a logical technique, named Indirect Mapping. This paper proposes an improvement to the technique used by NuGeM, whose original contribution is management of OIDs with a fewer number of disc accesses and less processing, thus reducing management time from the pages and eliminating the problem with exhaustion of OIDs. Also, the technique presented here can be applied to others OODBMSs. © 2011 IEEE.

Classification of masses in mammographic image using wavelet domain features and polynomial classifier

Breast cancer is the most common cancer among women. In CAD systems, several studies have investigated the use of wavelet transform as a multiresolution analysis tool for texture analysis and could be interpreted as inputs to a classifier. In classification, polynomial classifier has been used due to the advantages of providing only one model for optimal separation of classes and to consider this as the solution of the problem. In this paper, a system is proposed for texture analysis and classification of lesions in mammographic images. Multiresolution analysis features were extracted from the region of interest of a given image. These features were computed based on three different wavelet functions, Daubechies 8, Symlet 8 and bi-orthogonal 3.7. For classification, we used the polynomial classification algorithm to define the mammogram images as normal or abnormal. We also made a comparison with other artificial intelligence algorithms (Decision Tree, SVM, K-NN). A Receiver Operating Characteristics (ROC) curve is used to evaluate the performance of the proposed system. Our system is evaluated using 360 digitized mammograms from DDSM database and the result shows that the algorithm has an area under the ROC curve Az of 0.98 ± 0.03. The performance of the polynomial classifier has proved to be better in comparison to other classification algorithms. © 2013 Elsevier Ltd. All rights reserved.

Proposta de um dicionário eletrônico terminológico onomasiológico bilíngue inglês-português no domínio das redes neurais artificiais

Pós-graduação em Estudos Linguísticos - IBILCE

A emergência do marcador discursivo assim sob a óptica da gramaticalização: um caso de multifuncionalidade e (inter)subjetivização

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Concepção, desenvolvimento e aplicação do banco de imagens georreferenciadas no contexto do mapeamento terrestre móvel

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Report on the retrieval of data for small areas of microcomputers ( REDATAM) National Training Workshop

Through this workshop, database experts from the various ministries and the Central Statistical Office (CSO) were introduced to the CREATE and PROCESS modules of the REDATAM software, which could be used for database creation and analysis of data. This workshop was the second in a series of workshops aimed at promoting human-resource and capacity-building at the national and regional levels in the use of the REDATAM software. It also served as a qualifier for a follow-up workshop on the use of the web-publishing application of the software to be held in 2010.

Elementos de interoperabilidade na catalogação descritiva: configurações contemporâneas para a modelagem de ambientes informacionais digitais

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Testing search strategies for systematic reviews in the Medline literature database through PubMed

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Rede de tags para recuperação da informação no contexto da Representação Iterativa

Information retrieval is a recurrent subject in search of information science. This kind of study aim to improve results in both searches on the Web and in various other digital information environment. In this context, the Iterative Representation model suggested for digital repositories, appears as a differential that changes the paradigm of self-archiving of digital objects, creating a concept of relationship between terms that link the user thought the material deposited in the digital environment. The links effect by the Iterative Representation aided Assisted Folksonomy generate a shaped structure that connects networks, vertically and horizontally, the objects deposited, relying on some kind of structure for representing knowledge of specialty areas and therefore, creating an information network based on knowledge of users. The network of information created, called the network of tags is dynamic and effective a different model of information retrieval and study of digital information repositories.Keywords Digital Repositories; Iterative Representation; Folksonomy; Folksonomy Assisted; Semantic Web; Network Tags.

The Automatic Mapping of Princeton WordNet Lexical-Conceptual Relations onto the Brazilian Portuguese WordNet Database

Princeton WordNet (WN.Pr) lexical database has motivated efficient compilations of bulky relational lexicons since its inception in the 1980's. The EuroWordNet project, the first multilingual initiative built upon WN.Pr, opened up ways of building individual wordnets, and interrelating them by means of the so-called Inter-Lingual-Index, an unstructured list of the WN.Pr synsets. Other important initiative, relying on a slightly different method of building multilingual wordnets, is the MultiWordNet project, where the key strategy is building language specific wordnets keeping as much as possible of the semantic relations available in the WN.Pr. This paper, in particular, stresses that the additional advantage of using WN.Pr lexical database as a resource for building wordnets for other languages is to explore possibilities of implementing an automatic procedure to map the WN.Pr conceptual relations as hyponymy, co-hyponymy, troponymy, meronymy, cause, and entailment onto the lexical database of the wordnet under construction, a viable possibility, for those are language-independent relations that hold between lexicalized concepts, not between lexical units. Accordingly, combining methods from both initiatives, this paper presents the ongoing implementation of the WN.Br lexical database and the aforementioned automation procedure illustrated with a sample of the automatic encoding of the hyponymy and co-hyponymy relations.

Gestão de imagens em movimento de matérias jornalísticas em banco de dados na TV Digital

Pós-graduação em Televisão Digital: Informação e Conhecimento - FAAC

Image segmentation through combined methods: watershed transform, unsupervised distance learning and normalized cut

Research on image processing has shown that combining segmentation methods may lead to a solid approach to extract semantic information from different sort of images. Within this context, the Normalized Cut (NCut) is usually used as a final partitioning tool for graphs modeled in some chosen method. This work explores the Watershed Transform as a modeling tool, using different criteria of the hierarchical Watershed to convert an image into an adjacency graph. The Watershed is combined with an unsupervised distance learning step that redistributes the graph weights and redefines the Similarity matrix, before the final segmentation step using NCut. Adopting the Berkeley Segmentation Data Set and Benchmark as a background, our goal is to compare the results obtained for this method with previous work to validate its performance.

SNIIC: a plataforma digital de cultura brasileira sob a perspectiva das convergências entre o Design e a Ciência da Informação

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

SNIIC: a plataforma digital de cultura brasileira sob a perspectiva das convergências entre o Design e a Ciência da Informação

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Semantic information extraction from images of complex documents

Even though the digital processing of documents is increasingly widespread in industry, printed documents are still largely in use. In order to process electronically the contents of printed documents, information must be extracted from digital images of documents. When dealing with complex documents, in which the contents of different regions and fields can be highly heterogeneous with respect to layout, printing quality and the utilization of fonts and typing standards, the reconstruction of the contents of documents from digital images can be a difficult problem. In the present article we present an efficient solution for this problem, in which the semantic contents of fields in a complex document are extracted from a digital image.